Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 269 for “"Natural language processing (NLP)"”.
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Identifying External Cross-references using Natural Language Processing (NLP)
… projects. [Principal idea and novelty] We use Natural Language Processing (NLP), Pattern Recognition and Web Scrapping techniques for automatically extracting external cross-references from contractual requirements and prepare a map for representing related external cross-references to each …
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DOCUMENT-LEVEL RELATION EXTRACTION AND TEMPORAL REASONING WITH LARGE LANGUAGE MODELS
Large Language Models (LLMs) have become the backbone models for many natural language processing (NLP) tasks. In this thesis, we study the applications and limitations of LLMs in two aspects: (1) Document-level Relation Extraction (DocRE), and (2) Temporal Reasoning.
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Network Effect on Teams, Team Processes, and Performance
… processes. Through the use of text analysis and natural language processing (NLP) techniques, we illustrate how teams become more efficient in their work processes and develop a shared problem-solving framework, which in turn are beneficial for team performance. These computational tools allow us …
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Artificial intelligence (AI) in the public service: Public administrator perspectives on leveraging AI to support citizen and stakeholder engagement
… decision makers. One potential solution lies in Natural Language Processing (NLP), a branch of artificial intelligence (AI) that can automatically filter, parse, understand, interpret, and synthesize large amounts of human language. This research assesses the potential of AI for managing the …
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Extending the Information Partition Function: Modeling Interaction Effects in Highly Multivariate, Discrete Data
… methods, discuss various statistical methods of natural language processing (NLP), and discuss a general class of models described by Erosheva (2002) called generalized mixed membership models. We then propose extensions of the information partition function (IPF) derived by Engler (2002), …
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A system analysis of improvements in machine learning
Machine learning algorithms used for natural language processing (NLP) currently take too long to complete their learning function. This slow learning performance tends to make the model ineffective for an increasing requirement for real time applications such as voice transcription, language …
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Going Deeper with Images and Natural Language
… to interact with us about its surroundings in natural languages. Thanks to the progress made in deep learning, we've seen huge breakthroughs towards this goal over the last few years. The developments have been extremely rapid in visual recognition, in which machines now can categorize images …
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Dual Fixed-Size Ordinally Forgetting Encoding (FOFE) For Natural Language Processing
… ordinally-forgetting encoding (FOFE) on Natural Language Processing (NLP) tasks, called dual-FOFE. The main idea behind dual-FOFE is that it allows the encoding to be done with two different forgetting factors; this would resolve the original FOFEs dilemma in choosing between the benefits …
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Efficient Adaptation of Large Language Models in Natural Language Processing
The rapid growth of Large Language Models (LLMs) has significantly improved performance across a wide range of Natural Language Processing (NLP) tasks, including Information Retrieval (IR). Despite their strong generalisation capabilities, LLMs still require domain- and task-specific fine-tuning to …
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Detección de estados de ánimo mediante sentiment analysis en hispanohablantes
… treatment, and Sentiment Analysis based on only Natural Language Processing (NLP) concepts for text analysis. A mobile application with chatbot interface and a bot that invites the user to give details about their mood through questions validated by an expert, are the tools used to collect all …
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Conformal Methods for Efficient and Reliable Deep Learning
… scenarios. Empirically, we primarily focus on natural language processing (NLP) applications, together with substantial extensions to tasks in computer vision, drug discovery, and medicine.
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Coreference resolution on entities and events for hospital discharge summaries
… in electronic medical records (EMRs) and Natural Language Processing (NLP) technologies that can automatically extract information from them have opened the doors to automatic patient-care quality monitoring and medical- assist question answering systems. This thesis studies coreference …
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Comparison of natural language processing algorithms for medical texts
With the large corpora of clinical texts, natural language processing (NLP) is growing to be a field that people are exploring to extract useful patient information. NLP applications in clinical medicine are especially important in domains where the clinical observations are crucial to define and …
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Using Machine Learning for Description and Inference of Cyber Threats, Vulnerabilities, and Mitigations
Machine learning and natural language processing (NLP) can help describe and make inferences on the vast amount of text data in cybersecurity. We use a graph database named BRON, which contains data from publicly available threat and vulnerability sources, for machine learning inference. Applying …
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Toward a Natural Language Processing-based Model for Workplace Culture Scoring
… behavior of firms. In this project, I propose a natural language processing (NLP) framework to generate culture scores for individual employee reviews, leveraging text data from Glassdoor. I combine topic modeling to identify interpretable cultural themes with self-supervised learning to generate …
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Detecting Deceptive Impression Management Behaviors in Interviews Using Natural Language Processing
… desirability concerns. Given this limitation, natural language processing (NLP) has potential as a tool to unobtrusively assess raw interview content and measure deceptive IM. This study examined the use of open and closed-vocabulary NLP approaches for the detection of deceptive IM in mock …
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Transfer learning and robustness for natural language processing
Teaching machines to understand human language is one of the most elusive and long-standing challenges in Natural Language Processing (NLP). Driven by the fast development of deep learning, state-of-the-art NLP models have already achieved human-level performance in various large benchmark …
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A vector space approach for aspect-based sentiment analysis
Vector representations for language have been shown to be useful in a number of Natural Language Processing (NLP) tasks. In this thesis, we aim to investigate the effectiveness of word vector representations for the research problem of Aspect-Based Sentiment Analysis (ABSA), which attempts to …
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Unified processing of natural language and relational data
This work outlines a method for performing natural language tasks as part of a relational framework. Utilizing features of PostgreSQL as a relational database and its extensibility to allow for word embedding without leaving the relational database. This system can be extended to incorporate …
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The effectiveness of employee tracking technologies.
… interviews and analyze them manually, and I use natural language processing (NLP) to analyze interviews in an algorithmic approach to extract topics. Several employee outcomes of hybrid surveillance result, such as increased motivation and flexibility, dignity affronts, and employee distrust. …
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